Evidence map›Paper›PMID 37799462›Full record

ArticleFrontiers in oncology2023

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength.

Mark S Shiroishi, Dane Weinert, Steven Y Cen, Bino Varghese, Timothy Dondlinger, Melissa Prah, Jesse Mendoza, Sina Nazemi, Nima Ameli, Negin Amini and 21 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors at 11 institutions in 1 country.

Mark S ShiroishiDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Dane WeinertDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Steven Y CenDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Bino VargheseDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Timothy DondlingerImaging Biometrics, Elm Grove, WI, United States.
Melissa PrahDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States.
Jesse MendozaDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Sina NazemiDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Nima AmeliDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Negin AminiDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Salman ShohasDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Shannon ChenDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Bavrina BigjahanDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Gabriel ZadaDepartment of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States.
Thomas ChenDepartment of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States.
Josh Neman-EbrahimDepartment of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States.
Eric L ChangDepartment of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States.
Frances E ChowDepartment of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States.
Zhaoyang FanDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Wensha YangDepartment of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States.
Frank J AttenelloDepartment of Neurological Surgery, Keck School of Medicine of USC, Los Angeles, CA, United States.
Jason YeDepartment of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, CA, United States.
Paul E KimDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Vishal N PatelDepartment of Radiology, Mayo Clinic, Jacksonville, FL, United States.
Alexander LernerDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Jay AcharyaDepartment of Radiology, Keck School of Medicine of the University of Southern California (USC), Los Angeles, CA, United States.
Leland S HuDepartment of Radiology, Mayo Clinic, Phoenix, AZ, United States.
C Chad QuarlesCancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Jerrold L BoxermanDepartment of Diagnostic Imaging, The Warren Alpert Medical School of Brown University, Providence, RI, United States.
Ona WuAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Kathleen M SchmaindaDepartment of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States.
University of Southern California · USKeck Hospital of USC · USNeurological Surgery · USMedical College of Wisconsin · USAthinoula A. Martinos Center for Biomedical Imaging · USBrown University · USImaging Biometrics (United States) · USMarina Del Rey Hospital · USMayo Clinic Hospital · USMayo Clinic in Florida · USThe University of Texas MD Anderson Cancer Center · US

Funding

Quantitative (Perfusion and Diffusion) MRI Biomarkers to Measure Glioma ResponseU01CA176110 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2014 to 2023
$4.9M
Establishing the Validity of Brain Tumor Perfusion ImagingR01CA213158 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Christopher Chad Quarles · 2017 to 2026
$2.9M
New treatment monitoring biomarkers for brain tumors using multiparametric MRI with machine learningR01CA255123 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI SCHMAINDA, KATHLEEN MARIE · 2021 to 2025
$2.6M
Multi-site Validation and Application of a Consensus DSC MRI ProtocolR01CA221938 · NCI · ST. JOSEPH'S HOSPITAL AND MEDICAL CENTER · PI BOXERMAN, JERROLD L, HU, LELAND · 2018 to 2020
$738k
Advanced prediction of GBM recurrence (TIME) for personalized radiotherapyR21CA267139 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YANG, WENSHA · 2022 to 2024
$411k
NCI NIH HHS R01 CA213158NCI NIH HHS R01 CA221938NCI NIH HHS R01 CA255123NCI NIH HHS R21 CA267139NCI NIH HHS U01 CA176110
6 · The paper itself

Abstract

Introduction: 1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle ("low-FA") with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle ("intermediate-FA") and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients. Methods: This was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson's, Spearman's and intraclass correlation coefficients (ICC). Results: Twenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV. Conclusion: Our study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload.

Indexed as

1.5 Tesladynamic susceptibility contrast MRI (DSC-MRI)flip anglegliomastandardization

Identifiers

PMID37799462
PMCPMC10548232
OpenAlexW4386942032

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.